Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Drive devices and APIs from their W3C Thing Description. You gate every operation.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
THINGCTX_POLICY, THINGCTX_APPROVE_WHEN, THINGCTX_FS_ROOTDu brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"thingctx": {
"command": "uvx",
"args": [
"thingctx",
"--from",
"thingctx[mcp,http,mqtt,media,filesystem,authz]",
"thingctx-mcp",
"https://td.thingctx.com/index.json"
],
"env": {
"THINGCTX_POLICY": "your-value",
"THINGCTX_APPROVE_WHEN": "your-value",
"THINGCTX_FS_ROOT": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add thingctx --env THINGCTX_POLICY=your-value --env THINGCTX_APPROVE_WHEN=your-value --env THINGCTX_FS_ROOT=your-value -- uvx thingctx --from 'thingctx[mcp,http,mqtt,media,filesystem,authz]' thingctx-mcp https://td.thingctx.com/index.jsonTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"thingctx": {
"command": "uvx",
"args": [
"thingctx",
"--from",
"thingctx[mcp,http,mqtt,media,filesystem,authz]",
"thingctx-mcp",
"https://td.thingctx.com/index.json"
],
"env": {
"THINGCTX_POLICY": "your-value",
"THINGCTX_APPROVE_WHEN": "your-value",
"THINGCTX_FS_ROOT": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"thingctx": {
"type": "stdio",
"command": "uvx",
"args": [
"thingctx",
"--from",
"thingctx[mcp,http,mqtt,media,filesystem,authz]",
"thingctx-mcp",
"https://td.thingctx.com/index.json"
],
"env": {
"THINGCTX_POLICY": "your-value",
"THINGCTX_APPROVE_WHEN": "your-value",
"THINGCTX_FS_ROOT": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
THINGCTX_POLICY envTHINGCTX_APPROVE_WHEN envTHINGCTX_FS_ROOT envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde über die Domain thingctx.com bestätigt (die Registry prüft, wem die Domain gehört)
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.2.2) kam vor 3 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
thingctx turns a description of any API, device, or local process into tools an AI agent can call: authorized per operation, over the system's own transport, and the agent never holds your keys. The description is a W3C Web of Things Thing Description (a TD), a plain JSON file naming what the system can do. Write one, or compile it from an OpenAPI spec. The described system is the server, so you run no server per integration.
A "Thing" is whatever you want to describe: a REST API, an app, a sensor, a media server, a local object, or one system that is several of those at once. A media server takes commands over HTTP and serves its stream over RTSP. The pump in examples/ reads over MQTT and acts through a local call. Each is one Thing and one description.
A description names actions, properties, and events, and gives each one a form: the entry that says where and how to reach it. The URL scheme in that address picks the transport per call, so however many protocols one Thing spans, the agent still sees one tool set.
docs/BINDINGS.md covers the transports and how to add your own. A subprocess transport, exec, also ships, and it ships locked: it refuses every command until you hand it an explicit allowlist.
Those three stay distinct all the way to the call. A read, a write, and a subscribe do not collapse into one undifferentiated function, which is why the gate can allow the read and refuse the write on the same system. A flat list of functions has no such handle.
Pick your path: use it as a library if you own the agent loop, the command line if you do not want to write code, the MCP bridge if your host only speaks MCP, or add a transport if thingctx does not speak your protocol yet.
Stuck, or wondering whether something is possible? Ask in Discussions. Want to build something small? The open issues say what would help.
One paste shows the whole idea. The description is inline and the handler ships with the package, so nothing here needs a key, a network, or a second file:
pip install thingctx
import asyncio
import thingctx from thingctx.contrib.time import make_time_handler
TD = { "@context": "https://www.w3.org/2022/wot/td/v1.1", "id": "urn:thingctx:time", "title": "Time", "securityDefinitions": {"nosec_sc": {"scheme": "nosec"}}, "security": ["nosec_sc"], "actions": { "getCurrentTime": { "description": "Current time in an IANA timezone (default UTC).", "input": { "type": "object", "properties": {"timezone": {"type": "string"}}, }, "safe": True, "idempotent": True, "forms": [{"href": "local://getCurrentTime"}], } }, }
async def main(): client = thingctx.ThingClient(tds=[TD], bindings=[thingctx.LocalBinding(make_time_handler())]) tools, invoke = client.as_tools() # specs for your model; invoke runs a call print("tools:", t["function" for t in tools]) print(await invoke("time__getCurrentTime", {"timezone": "UTC"}))
asyncio.run(main())
tools: ['time__getCurrentTime'] {'timezone': 'UTC', 'datetime': '2026-07-26T15:59:03.233080+00:00', 'utc_offset': '+0000'}
That is the whole loop: a description in, tools out, calls routed. LocalBinding is a binding, a transport implementation; this one routes the local:// address to the handler you pass it. Every other transport works the same way; only the form's href changes.
pip install 'thingctx[llm,http,validate]'
Quote the argument; unquoted brackets fail in zsh. Base pip install thingctx has no dependencies; it already includes the local and exec transports. Redis support is pip install 'thingctx[redis]'. Every optional transport and capability has an extra, listed in pyproject.toml; each one this page uses is named next to the code that needs it.
A description can be small. This one drives the live, key free Open-Meteo forecast API, so it runs as written. Save it as weather.td.json, a later example uses it:
{
"@context": "https://www.w3.org/2022/wot/td/v1.1", "id": "urn:example:weather:v1", "title": "Weather", "securityDefinitions": { "nosec_sc": { "scheme": "nosec" } }, "security": ["nosec_sc"], "actions": { "forecast": { "input": { "type": "object", "properties": { "latitude": { "type": "number" }, "longitude": { "type": "number" }, "current": { "type": "string" } }, "required": ["latitude", "longitude"] }, "forms": [{ "href": "https://api.open-meteo.com/v1/forecast", "htv:methodName": "GET" }] } } }
thingctx projects each action to a tool named __ : this file yields weather__forecast (a version segment on the id is dropped). docs/MAPPING.md specifies the full projection. The description carries no secrets, so it is safe to commit and share. The secret is supplied at runtime to the binding that carries the call. Secrets are keyed per Thing.
If your system already has an OpenAPI 3.x spec, you do not have to author a description at all:
pip install 'thingctx[openapi]'
thingctx import openapi https://api.example.com/openapi.json --out api.td.json
The spec can be a file or a URL, JSON or YAML; --base-url, --id, and --title override what the spec says. The result is a normal description, so everything else here applies to it unchanged.
Ready made descriptions for common apps, developer tools, and devices live at td.thingctx.com.
Own the agent loop? Read descriptions, hand the specs to your model, and route each call back through invoke. ThingClient needs no LLM and has no opinion on what chose the action; any code can drive it. This sketch shows the surface against a folder describing a pump; from_arg turns a path or URL into a registry of descriptions:
import thingctx
async def run(): # a sketch, not a program: call it from your own loop client = thingctx.ThingClient.from_registry(thingctx.from_arg("./descriptions/")) specs, invoke = client.as_tools()
await invoke("pump__set_speed", {"rpm": 1500}) await client.read_property("pump__rpm") await client.write_property("pump__target_rpm", 1500) # gated like invoke async for evt in await client.subscribe( "pump__overheat" ): # subscribe returns an async iterator ...
The form picks the transport per call, so one client can read over HTTP, subscribe over MQTT, and read or write cached properties over Redis. Bindings that pull optional dependencies, including MQTT and Redis, are off by default: install the extra and pass bindings=thingctx.BindingRegistry.default(mqtt=True, redis=True).
Want the loop handled for you? The llm extra runs any provider through litellm; add the http extra, since the weather file's form is HTTPS. Set your provider key in its usual variable (OPENAI_API_KEY, ANTHROPIC_API_KEY, and so on) and pick a model with THINGCTX_MODEL:
import asyncio
import thingctx
async def main():
host = thingctx.from_file("weather.td.json") print(await host.chat("What is the forecast for Cairo? Latitude 30.0, longitude 31.2."))
asyncio.run(main())
The model calls weather__forecast itself and answers in prose:
The forecast for Cairo is clear, around 34 C.
Two opt in layers stand between an agent and a real system; both run before any transport is selected. Neither layer handles a credential. The binding holds the secret and the model never sees it.
Approval gates risky calls behind a human. Risk is read from the description, and when to gate is yours: declared (only actions the description marks risky; the default), destructive (adds non idempotent actions and every property write), all, or never. A gated call with no approver is denied: a gate with nobody to open it stays shut. The check sits inside invoke and write_property, so it covers the LLM loop, direct callers, and the MCP bridge alike.
Carrying on from the first example above, with the same TD:
def approve(req): # sync or async; return True to allow
return input(f"run {req.tool_name}{req.arguments}? [y/N] ").lower() == "y"
client = thingctx.ThingClient( tds=[TD], bindings=[thingctx.LocalBinding(make_time_handler())], approve=approve, approve_when="all", )
Authorization decides from policy, per caller, per operation. Pass a pdp and an identity and every call authorizes the resolved (thing, affordance, operation) before it reaches the system; an affordance is an action, property, or event named in the description. This snippet condenses examples/14_authz.py, which runs as is on the core install. It defines the TD and Pump used below: a pump with one property, target_rpm.
from thingctx import LocalBinding, ThingClient
from thingctx.authz import LocalPolicyGrantSource, PolicyDecisionPoint, build_vocabulary
reader = ThingClient( tds=[TD], bindings=[LocalBinding(Pump())] ) # no pdp yet; parsed only to read the description vocab = build_vocabulary(reader.things) # the closed set the description declares
grants = LocalPolicyGrantSource({"operator": {("urn:demo:pump", "target_rpm", "readproperty")}}) pdp = PolicyDecisionPoint(vocabulary=vocab, grant_source=grants) identity = {"sub": "alice", "roles": ["operator"]} # claims, validated upstream
client = ThingClient(tds=[TD], bindings=[LocalBinding(Pump())], pdp=pdp, identity=identity)
Alice's operator role grants read on target_rpm and nothing else, so her reads pass and her writes are refused. The vocabulary is closed: a grant is honored only for operations the description declares. thingctx.authz imports no crypto and runs on the dependency free core. Identity is claims that something upstream validated, never the credential itself.
Running the example prints:
vocabulary (grantable tuples the TD declares):
(urn:demo:pump, target_rpm, readproperty) (urn:demo:pump, target_rpm, writeproperty)
READ target_rpm -> ALLOWED, device returned 1200 WRITE target_rpm -> DENIED, grant does not include ('urn:demo:pump', 'target_rpm', 'writeproperty')
RE-READ target_rpm -> 1200 (unchanged: the denied write never ran)
The full model is in docs/SECURITY.md.
Some agents only take tools over MCP. For those, thingctx ships one generic MCP server, with no per integration server. It serves any registry of descriptions: a folder, a URL, or a W3C Thing Description Directory. A Directory is the standard catalog server for descriptions.
pip install 'thingctx[mcp,http]'
thingctx-mcp ./descriptions/
For Claude D
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